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NAIR: Network Analysis of Immune Repertoire
T cells represent a crucial component of the adaptive immune system and mediate anti-tumoral immunity as well as protection against infections, including respiratory viruses such as SARS-CoV-2. Next-generation sequencing of the T-cell receptors (TCRs) can be used to profile the T-cell repertoire. We...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443597/ https://www.ncbi.nlm.nih.gov/pubmed/37614227 http://dx.doi.org/10.3389/fimmu.2023.1181825 |
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author | Yang, Hai Cham, Jason Neal, Brian Patrick Fan, Zenghua He, Tao Zhang, Li |
author_facet | Yang, Hai Cham, Jason Neal, Brian Patrick Fan, Zenghua He, Tao Zhang, Li |
author_sort | Yang, Hai |
collection | PubMed |
description | T cells represent a crucial component of the adaptive immune system and mediate anti-tumoral immunity as well as protection against infections, including respiratory viruses such as SARS-CoV-2. Next-generation sequencing of the T-cell receptors (TCRs) can be used to profile the T-cell repertoire. We developed a customized pipeline for Network Analysis of Immune Repertoire (NAIR) with advanced statistical methods to characterize and investigate changes in the landscape of TCR sequences. We first performed network analysis on the TCR sequence data based on sequence similarity. We then quantified the repertoire network by network properties and correlated it with clinical outcomes of interest. In addition, we identified (1) disease-specific/associated clusters and (2) shared clusters across samples based on our customized search algorithms and assessed their relationship with clinical outcomes such as recovery from COVID-19 infection. Furthermore, to identify disease-specific TCRs, we introduced a new metric that incorporates the clonal generation probability and the clonal abundance by using the Bayes factor to filter out the false positives. TCR-seq data from COVID-19 subjects and healthy donors were used to illustrate that the proposed approach to analyzing the network architecture of the immune repertoire can reveal potential disease-specific TCRs responsible for the immune response to infection. |
format | Online Article Text |
id | pubmed-10443597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104435972023-08-23 NAIR: Network Analysis of Immune Repertoire Yang, Hai Cham, Jason Neal, Brian Patrick Fan, Zenghua He, Tao Zhang, Li Front Immunol Immunology T cells represent a crucial component of the adaptive immune system and mediate anti-tumoral immunity as well as protection against infections, including respiratory viruses such as SARS-CoV-2. Next-generation sequencing of the T-cell receptors (TCRs) can be used to profile the T-cell repertoire. We developed a customized pipeline for Network Analysis of Immune Repertoire (NAIR) with advanced statistical methods to characterize and investigate changes in the landscape of TCR sequences. We first performed network analysis on the TCR sequence data based on sequence similarity. We then quantified the repertoire network by network properties and correlated it with clinical outcomes of interest. In addition, we identified (1) disease-specific/associated clusters and (2) shared clusters across samples based on our customized search algorithms and assessed their relationship with clinical outcomes such as recovery from COVID-19 infection. Furthermore, to identify disease-specific TCRs, we introduced a new metric that incorporates the clonal generation probability and the clonal abundance by using the Bayes factor to filter out the false positives. TCR-seq data from COVID-19 subjects and healthy donors were used to illustrate that the proposed approach to analyzing the network architecture of the immune repertoire can reveal potential disease-specific TCRs responsible for the immune response to infection. Frontiers Media S.A. 2023-07-07 /pmc/articles/PMC10443597/ /pubmed/37614227 http://dx.doi.org/10.3389/fimmu.2023.1181825 Text en Copyright © 2023 Yang, Cham, Neal, Fan, He and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Yang, Hai Cham, Jason Neal, Brian Patrick Fan, Zenghua He, Tao Zhang, Li NAIR: Network Analysis of Immune Repertoire |
title | NAIR: Network Analysis of Immune Repertoire |
title_full | NAIR: Network Analysis of Immune Repertoire |
title_fullStr | NAIR: Network Analysis of Immune Repertoire |
title_full_unstemmed | NAIR: Network Analysis of Immune Repertoire |
title_short | NAIR: Network Analysis of Immune Repertoire |
title_sort | nair: network analysis of immune repertoire |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10443597/ https://www.ncbi.nlm.nih.gov/pubmed/37614227 http://dx.doi.org/10.3389/fimmu.2023.1181825 |
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